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We show that the lower bound for the optimal directional discrepancy with respect to the class of rectangles in $\mathbb{R}^2$ rotated in a restricted interval of directions $[-\theta, \theta]$ with $\theta < \frac{\pi}{4}$ is of the order…

Classical Analysis and ODEs · Mathematics 2022-09-27 Dmitriy Bilyk , Michelle Mastrianni

Let $\alpha$ be an irrational number, let $X_1, X_2, \ldots$ be independent, identically distributed, integer-valued random variables, and put $S_k=\sum_{j=1}^k X_j$. Assuming that $X_1$ has finite variance or heavy tails $P (|X_1|>t)\sim…

Probability · Mathematics 2023-03-15 Istvan Berkes , Bence Borda

Divergence functions are measures of distance or dissimilarity between probability distributions that serve various purposes in statistics and applications. We propose decompositions of Wasserstein and Cram\'er distances$-$which compare two…

Methodology · Statistics 2025-08-08 Johannes Resin , Daniel Wolffram , Johannes Bracher , Timo Dimitriadis

We consider the asymptotic distribution of the IP sparsity function, which measures the minimal support of optimal IP solutions, and the IP to LP distance function, which measures the distance between optimal IP and LP solutions. We create…

Optimization and Control · Mathematics 2020-09-10 Timm Oertel , Joseph Paat , Robert Weismantel

The paper addresses a problem of sampling discretization of integral norms of elements of finite-dimensional subspaces satisfying some conditions. We prove sampling discretization results under a standard assumption formulated in terms of…

Functional Analysis · Mathematics 2023-04-13 F. Dai , E. Kosov , V. Temlyakov

The distribution of the properly renormalized gaps of $\sqrt{n} \,\mathrm{mod}\, 1$ with $n < N$ converges (when $N\rightarrow \infty$) to a non-standard limit distribution, as Elkies and McMullen proved in 2004 using techniques from…

Number Theory · Mathematics 2025-09-18 Maksym Radziwiłł , Niclas Technau

We consider the local discrepancy of a symmetrized version of Hammersley type point sets in the unit square. As a measure for the irregularity of distribution we study the norm of the local discrepancy in Besov spaces with dominating mixed…

Number Theory · Mathematics 2020-05-28 Ralph Kritzinger

We investigate numerical differentiation formulas on irregular centers in two or more variables that are exact for polynomials of a given order and minimize an absolute seminorm of the weight vector. Error bounds are given in terms of a…

Numerical Analysis · Mathematics 2025-08-26 Oleg Davydov , Robert Schaback

By a result of Heinrich, Novak, Wasilkowski and Wo\'zniakowski the inverse of the star discrepancy $n(d,\varepsilon)$ satisfies $n(d,\varepsilon)\leq c_{\abs}d\varepsilon^{-2}$. Equivalently for any $N$ and $d$ there exists a set of $N$…

Probability · Mathematics 2014-08-12 Thomas Löbbe

We present a novel family of nonparametric omnibus tests of the hypothesis that two unknown but estimable functions are equal in distribution when applied to the observed data structure. We developed these tests, which represent a…

Statistics Theory · Mathematics 2017-06-15 Alexander R. Luedtke , Marco Carone , Mark J. van der Laan

We study the problem of nonparametric estimation of the fractional derivative of unknown distribution function and of spectral function and show that these problems are well posed when the order of derivative is less than 0.5. We prove also…

Statistics Theory · Mathematics 2014-12-23 E. Ostrovsky , L. Sirota

Uniform deviation bounds limit the difference between a model's expected loss and its loss on an empirical sample uniformly for all models in a learning problem. As such, they are a critical component to empirical risk minimization. In this…

Machine Learning · Statistics 2017-02-28 Olivier Bachem , Mario Lucic , S. Hamed Hassani , Andreas Krause

Given i.i.d samples from some unknown continuous density on hyper-rectangle $[0, 1]^d$, we attempt to learn a piecewise constant function that approximates this underlying density non-parametrically. Our density estimate is defined on a…

Machine Learning · Statistics 2015-09-24 Kun Yang , Hao Su , Wing Hung Wang

We address the problem of detection and estimation of one or two change-points in the mean of a series of random variables. We use the formalism of set estimation in regression: To each point of a design is attached a binary label that…

Statistics Theory · Mathematics 2018-09-07 Victor-Emmanuel Brunel

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

Stolarsky's invariance principle quantifies the deviation of a subset of a metric space from the uniform distribution. Classically derived for spherical sets, it has been recently studied in a number of other situations, revealing a general…

Combinatorics · Mathematics 2021-09-03 Alexander Barg

We generalized the Korkin-Zolotarev theorem to the case of entire functions having the smallest $L^1$ norm on a system of intervals $E$. If $\bbC\setminus E$ is a domain of Widom type with the Direct Cauchy Theorem we give an explicit…

Classical Analysis and ODEs · Mathematics 2012-04-23 Peter Yuditskii

In the regularly varying time series setting, a cluster of exceedances is a short period for which the supremum norm exceeds a high threshold. We propose to study a generalization of this notion considering short periods, or blocks, with…

Probability · Mathematics 2022-07-22 Gloria Buriticá , Thomas Mikosch , Olivier Wintenberger

We find the best asymptotic lower bounds for the coefficient of the leading term of the $L_1$ norm of the two-dimensional (axis-parallel) discrepancy that can be obtained by K.Roth's orthogonal function method among a large class of test…

Classical Analysis and ODEs · Mathematics 2022-11-29 Armen Vagharshakyan

Following a result of D.~Bylik and M.T.~Lacey from 2008 it is known that there exists an absolute constant $\eta>0$ such that the (unnormalized) $L^{\infty}$-norm of the three-dimensional discrepancy function, i.e, the (unnormalized) star…

Number Theory · Mathematics 2020-09-15 Florian Puchhammer
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